Cell pelotons: A model of early evolutionary cell sorting, with application to slime mold Dictyostelium discoideum.

A theoretical model is presented for early evolutionary cell sorting within cellular aggregates. The model involves an energy-saving mechanism and principles of collective self-organization analogous to those observed in bicycle pelotons (groups of cyclists). The theoretical framework is applied to slime-mold slugs (Dictyostelium discoideum) and incorporated into a computer simulation which demonstrates principally the sorting of cells between the anterior and posterior slug regions. The simulation relies on an existing simulation of bicycle peloton dynamics which is modified to incorporate a limited range of cell metabolic capacities among heterogeneous cells, along with a tunable energy-expenditure parameter, referred to as an "output-level" or "starvation-level" to reflect diminishing energetic supply. Proto-cellular dynamics are modeled for three output phases: "active", "suffering", and "dying or dead." Adjusting the starvation parameter causes cell differentiation and sorting into sub-groups within the cellular aggregate. Tuning of the starvation parameter demonstrates how weak or expired cells shuffle backward within the cellular aggregate.

American coot collective on-water dynamics.

American coot (Fulica americana) flocks exhibit water surface (two-dimensional) collective dynamics that oscillate between two primary phases: a disordered phase of low density and non-uniform coot body orientations; a synchronized phase characterized by high density, uniform body orientations and speed. For this small-scale study, data was obtained for flocks of 10 to ~250 members for these phases. Approximate durations of phase occurrences were recorded for different flock sizes and for both relatively calm and severe weather conditions. Results indicate that for timed durations of up to ~ 2 hours, small flocks (10 coots) exhibit a comparatively high disordered/synchronized phase ratio (PR) in relatively warm and well-sheltered conditions (substantially > 1); large flocks (~100 or more) generally exhibit a PR near 1, while large flocks spend comparatively more time in a disordered phase in relatively calm conditions (PR somewhat > 1), and spend more time in a synchronized phase during severe conditions (PR < 1). Data suggests a correlation between flock size and PR; and weather conditions and PR, whereby coupling principles driving on-water collective behavior include energy-savings and thermoregulation. Secondary phases occur, including expanding circle and sequential short distance flight, near-single-file lines, convex and concave arcs, among others.

A Computer Model of Drafting Effects on Collective Behavior in Elite 10,000-m Runners.

PURPOSE: Drafting in cycling influences collective behavior of pelotons. Although evidence for collective behavior in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modeled the effects of drafting on behavior in elite 10,000-m runners. METHODS: Using performance data from a men's elite 10,000-m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of 3 different drafting quantities on collective behavior: no drafting, drafting to 3 m behind with up to ~8% energy savings (a realistic running draft), and drafting up to 3 m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behavior were analyzed in each condition: mean speed, mean group stretch (distance between first- and last-placed runner), and runner-convergence ratio (RCR), which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners. RESULTS: Mean speeds were 6.32 ± 0.28, 5.57 ± 0.18, and 5.51 ± 0.13 m/s in the cycling-draft, runner-draft, and no-draft conditions, respectively (all P < .001). RCR was lower in the cycling-draft condition but did not differ between the other 2. Mean stretch did not differ between conditions. CONCLUSIONS: Collective behaviors observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are as yet unclear.

Energy saving mechanisms, collective behavior and the variation range hypothesis in biological systems: A review.

Energy saving mechanisms are ubiquitous in nature. Aerodynamic and hydrodynamic drafting, vortice uplift, Bernoulli suction, thermoregulatory coupling, path following, physical hooks, synchronization, and cooperation are only some of the better-known examples. While drafting mechanisms also appear in non-biological systems such as sedimentation and particle vortices, the broad spectrum of these mechanisms appears more diversely in biological systems that include bacteria, spermatozoa, various aquatic species, birds, land animals, semi-fluid dwellers like turtle hatchlings, as well as human systems. We present the thermodynamic framework for energy saving mechanisms, and we review evidence in favor of the variation range hypothesis. This hypothesis posits that, as an evolutionary process, the variation range between strongest and weakest group members converges on the equivalent energy saving quantity that is generated by the energy saving mechanism. We also review self-organized structures that emerge due to energy saving mechanisms, including convective processes that can be observed in many systems over both short and long time scales, as well as high collective output processes in which a form of collective position locking occurs.

Equivalences in Biological and Economical Systems: Peloton Dynamics and the Rebound Effect.

An interdisciplinary bridge is proposed between principles of collective behavior in biological systems, particularly bicycle pelotons, and the economic phenomenon called the rebound effect. Two main equivalencies are proposed between aspects of peloton dynamics and aspects of energy service efficiencies and the rebound effect. Firstly, a threshold whereby weaker cyclists, up to maximal capacities, sustain speeds of pacesetters by drafting; equivalent to a threshold whereby consumers will not exceed maximum allocated budgets for energy services, costs for which are externally determined. Secondly, a threshold of peloton dynamics whereby, below this threshold, weaker cyclists share costly non-drafting positions, whereas above this threshold cyclists cannot share these positions but can sustain pacesetter speeds. This is in turn equivalent to the threshold in the context of energy service efficiency, whereby consumers will increase spending to the limit indicated by the rebound magnitude but not to their maximum allocated budgets. These thresholds are a consequence of the model equations, and the latter threshold is explained by consumer apprehension that existing energy efficiencies could disappear or be negative, when consumers would be over budget. This partly explains long term rebound increase, whereby consumers increase consumption as confidence rises that cost savings due to energy service efficiency is stable.